The Conjunction Fallacy in Quantum Decision Theory

Коваленко, Т. В.; Sornette, Didier

doi:10.1007/978-3-030-97273-8_11

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…Subsequently, it has been demonstrated that quantum mechanics can explain certain psychological and decision-making processes better than any classical model [9,31,33,34]. A large and growing body of research has provided significant evidence speaking in favour of this hypothesis [8,21,22,[34][35][36][37][38][39][40][41][42][43][44][45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Quantum-Inspired Neural Network Model of Optical Illusions

Maksymov

2024

Algorithms

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Ambiguous optical illusions have been a paradigmatic object of fascination, research and inspiration in arts, psychology and video games. However, accurate computational models of perception of ambiguous figures have been elusive. In this paper, we design and train a deep neural network model to simulate human perception of the Necker cube, an ambiguous drawing with several alternating possible interpretations. Defining the weights of the neural network connection using a quantum generator of truly random numbers, in agreement with the emerging concepts of quantum artificial intelligence and quantum cognition, we reveal that the actual perceptual state of the Necker cube is a qubit-like superposition of the two fundamental perceptual states predicted by classical theories. Our results finds applications in video games and virtual reality systems employed for training of astronauts and operators of unmanned aerial vehicles. They are also useful for researchers working in the fields of machine learning and vision, psychology of perception and quantum–mechanical models of human mind and decision making.

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Section: Introductionmentioning

confidence: 99%

Quantum-Inspired Neural Network Model of Optical Illusions

Maksymov

2024

Algorithms

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“…While the Conjunction fallacy has already been examined and explained in terms of quantum interference [ 45 ], the novelty here is that the representation of subjective probability, identified via the absorption probability of a one-dimensional quantum walk, explains both the conjunction fallacy and S-shaped probabilistic distortions, connecting two seemingly disparate phenomena. Because probability perception is described as a trade-off between efficiency and accuracy (see sub-section “Perception of probability modeled by absorption probability”), the model comes with a qualitative prediction: people making the conjunction fallacy respond faster than those who do not, which is in agreement with empirical findings [ 72 ].…”

Section: Examples Of Application Of the Proposed Quantum Walk Framewo...mentioning

confidence: 99%

On the use of discrete-time quantum walks in decision theory

2022

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We present a short review of discrete-time quantum walks (DTQW) as a potentially useful and rich formalism to model human decision-making. We present a pedagogical introduction of the underlying formalism and main structural properties. We suggest that DTQW are particularly suitable for combining the two strands of literature on evidence accumulator models and on the quantum formalism of cognition. Due to the additional spin degree of freedom, models based on DTQW allow for a natural modeling of model choice and confidence rating in separate bases. Levels of introspection and self-assessment during choice deliberations can be modeled by the introduction of a probability for measurement of either position and/or spin of the DTQW, where each measurement act leads to a partial decoherence (corresponding to a step towards rationalization) of the deliberation process. We show how quantum walks predict observed probabilistic misperception like S-shaped subjective probability and conjunction fallacy. Our framework emphasizes the close relationship between response times and type of preferences and of responses. In particular, decision theories based on DTQW do not need to invoke two systems (“fast” and “slow”) as in dual process theories. Within our DTQW framework, the two fast and slow systems are replaced by a single system, but with two types of self-assessment or introspection. The “thinking fast” regime is obtained with no or little self-assessment, while the “thinking slow” regime corresponds to a strong rate of self-assessment. We predict a trade-off between speed and accuracy, as empirically reported.

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“…The other way is asking to make decisions independently, on a conjunction characteristic and separately on its constituent, as is considered by Shafir et al [256]. The setup of Tversky and Kahneman [255] has been considered in [94], the setup of Shafir et al [256], in [257]. Below we consider the independent way of making decisions as in the experiments of Shafir et al [256], but by using methodology different from that employed by [257], and involving no quantum techniques.…”

Section: Conjunction Fallacymentioning

confidence: 99%

“…The setup of Tversky and Kahneman [255] has been considered in [94], the setup of Shafir et al [256], in [257]. Below we consider the independent way of making decisions as in the experiments of Shafir et al [256], but by using methodology different from that employed by [257], and involving no quantum techniques.…”

Section: Conjunction Fallacymentioning

confidence: 99%

Quantum operation of affective artificial intelligence

Yukalov¹

2023

Laser Phys.

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The review analyses the fundamental principles which Artificial Intelligence should be based on in order to imitate the realistic process of taking decisions by humans experiencing emotions. Two approaches are considered, one based on quantum theory and the other employing classical terms. Both these approaches have a number of similarities, being principally probabilistic. The analogies between quantum measurements under intrinsic noise and affective decision making are elucidated. It is shown that cognitive processes have many features that are formally similar to quantum measurements. This, however, in no way means that for the imitation of human decision making Affective Artificial Intelligence has necessarily to rely on the functioning of quantum systems. The analogies between human decision making and quantum measurements merely demonstrate formal common properties in their functioning. It is in this sense that one has to understand quantum operation of Artificial Intelligence. Appreciating the common features between quantum measurements and decision making helps for the formulation of an axiomatic approach employing only classical notions. Artificial Intelligence, following this approach, operates similarly to humans, by taking into account the utility of the considered alternatives as well as their emotional attractiveness. Affective Artificial Intelligence, whose operation takes account of the cognition-emotion duality, avoids numerous behavioural paradoxes of traditional decision making. A society of intelligent agents, interacting through the repeated multistep exchange of information, forms a network accomplishing dynamic decision making based on the evaluation of utility and affected by the emotional attractiveness of alternatives. The considered intelligent networks can characterize the operation of either a human society of affective decision makers, or the brain composed of neurons, or a typical probabilistic network of an artificial intelligence.

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The Conjunction Fallacy in Quantum Decision Theory

Cited by 3 publications

References 14 publications

Quantum-Inspired Neural Network Model of Optical Illusions

Quantum-Inspired Neural Network Model of Optical Illusions

On the use of discrete-time quantum walks in decision theory

Quantum operation of affective artificial intelligence

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